The measurement of beat-to-beat QT interval variability (QTV) shows clinical promise for identifying several types of cardiac pathology, including coronary artery disease, acute myocardial ischemia and infarction, left ventricular hypertrophy, and various types of cardiomyopathy. Importantly, in patients referred for electrophysiologic studies and in animals who receive drugs that prolong the QT interval, increased repolarization lability as reflected by increased beat-to-beat QTV is strongly predictive of future arrhythmic events. As such, several researchers have recently developed software programs to quantify QTV.
However, there are a number of limitations associated with these existing software programs. First, most if not all such programs require the operator to actively perform certain functions, for example that the operator manually choose the onset and offset of an initial QT interval template. This step of human intervention is both time consuming and labor intensive, and affects the reproducibility of the result. Second, most existing programs also allow for QTV analyses in only one single channel at a time (i.e., usually in limb lead II or limb lead I), and not in multiple channels simultaneously. This can lead to spuriously high QTV values, particularly when the T wave in the channel being studied is small, noisy or otherwise poorly defined. Third, no known existing programs for QTV analyses perform in real time, only offline, with the exception of one real-time program that is focused on dynamic QT vs. RR plots and which in any case has the other limitations noted above. A lack of real-time capability necessarily entails that any acute or subacute change in QTV, as might occur for example during myocardial ischemia or the treatment thereof, cannot be readily observed or acted upon. Similar limitations also apply to all existing programs that attempt to measure PQ interval variability (PQV).
Schlegel et al., in U.S. Pat. No. 7,113,820, assigned to the same assignee as the present invention, provided a real-time ECG analysis system. In the system of the '820 patent, cardiac electrical data were received from a patient, manipulated to determine various useful aspects of the ECG signal, and displayed in real time in a useful form on a computer screen or monitor. The monitor displayed the high frequency data from the QRS complex in units of microvolts, juxtaposed with a display of conventional ECG data in units of millivolts or microvolts. The high frequency data were analyzed for their root mean square (RMS) voltage values and the discrete RMS values and related parameters were displayed in real time. The high frequency data from the QRS complex were analyzed with imbedded algorithms to determine the presence or absence of reduced amplitude zones, referred to as “RAZs”. RAZs were displayed as “go, no-go” signals on the computer monitor. The RMS and related values of the high frequency components were displayed as time varying signals, and the presence or absence of RAZs could be similarly displayed over time. This system has proved to be very successful, but did not provide the means to analyze QT or PQ variability, as in the systems referred to above.
On the other hand, in U.S. Pat. No. 5,560,368, Berger taught a method for semi-automated, offline QT variability measurement. In the '368 patent, Berger suggested a method for analyzing electrocardiograph signals that involved: sensing fluctuations in voltage resulting from electrical activity of a heart as signals having an analog value; converting such signals having an analog value to digital values corresponding substantially to the analog value of the signals; recording the digital values in a record; analyzing the digital values of the record offline by: identifying a time of each R wave of a heartbeat; manually defining a template QT interval for a heartbeat by selecting a beginning of a QRS complex and an end of a T wave for the heartbeat; determining an alteration value selected from the group consisting of an elongation of a heartbeat in time and a compression of a heartbeat in time as an error function for the heartbeat; performing a binary search to determine a minimal value for the error function; and assessing changes in QT interval for each heartbeat using the entire T wave. However, the Berger et al. method suffered from the same drawbacks as other QTV systems as described above.
In addition, in U.S. Pat. No. 6,438,409, Malik et al taught a method for offline analysis of T-wave morphology (TWM) that focused on the percentage contribution of the strictly “non-dipolar” components of the T-wave to the total energy of the T-wave as determined by utilizing singular value decomposition (SVD) and calculating the so-called “relative T-wave residuum”, TWR. Although Malik et al's TWR parameter may help to supplement other pre-existing measures of TWM, such as the so-called “complexity ratio” earlier introduced by Priori et al., the TWM parameters of Malik et al. are subject to certain critical limitations that adversely impact their clinical utility. For example, the TWR parameter is hampered by its poor reproducibility, and, especially when signal averaging is not performed, TWR may often in fact represent more noise than signal.
Thus, there remains a need for a computer based system that allows for: 1) fully automatic and real-time monitoring of a plurality of indices of QTV and PQV for each of a plurality of channels of an electrocardiogram; and for 2) improved parameters of TWM (and also of P-wave and QRS-wave morphology) that have improved clinical utility. The system should also provide automatically measured parameters which are more reproducible and reliable than all existing measures of QTV, PQV and TWM in terms of accurately predicting the presence of underlying cardiac pathology. The system should be adaptable to standard, in-place systems and require no operator interference with the selection of various criteria of the ECG waveforms. The present invention is directed to solving these and other drawbacks in the art.